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Variability hypothesis

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Two normal distributions with equal means but different standard deviations.
Two distribution curves with identical means but different variabilities. Note that the curve with the greater variability (green) yields higher values in both the lowest and highest ends of the range.

The variability hypothesis, also known as the greater male variability hypothesis, states that males display greater variability in traits than females do. It has often been discussed in relation to cognitive ability, where it has been observed that human males are more likely than females to have either very high or very low intelligence. The sex-difference in the variability of intelligence has been discussed since at least Charles Darwin.[1] Sex-differences in variability are present in many abilities and traits — including physical, psychological and genetic ones. It is not only found in humans but in other sexually dimorphic species as well.

History

The notion of greater male variability — at least in respect to physical characteristics — can be traced back to the writings of Charles Darwin. When he expounded his theory of sexual selection in The Descent of Man and Selection in Relation to Sex, Darwin noted that in many species, including humans, males tended to show greater variation than females in sexually selected traits:

"Throughout the animal kingdom, when the sexes differ from each other in external appearance, it is the male which, with rare exceptions, has been chiefly modified; for the female still remains more like the young of her own species, and more like the other members of the same group" (p. 272, vol 1, chapter VIII).[2]

To exemplify this greater male variability in humans, Darwin also cites some observations made by his contemporaries. For example, he highlights findings from the Novara Expedition of 1861–67 where "a vast number of measurements of various parts of the body in different races were made, and the men were found in almost every case to present a greater range of variation than the women" (p. 275). To Darwin, the evidence from the medical community at the time, which suggested a greater prevalence of physical abnormalities among men than women, was also indicative of man's greater physical variability.

Although Darwin was curious about sex differences in variability throughout the animal kingdom, variability in humans was not a chief concern of his research. The first scholar to carry out a detailed empirical investigation on the question of human sex differences in variability in both physical and mental faculties, was the sexologist Havelock Ellis. In his 1894 publication Man and Women: A study of human sexual characters, Ellis dedicated an entire chapter to the subject, entitled “The Variational Tendency of Men”[3]. In this chapter he posits that “both the physical and mental characters of men show wider limits of variation than do the physical and mental characters of women” (p. 358). Ellis documents several studies that support this assertion (see pp. 360–367), and

"By the 1890s several studies had been conducted to demonstrate that variability was indeed more characteristic of males...The biological evidence overwhelmingly favored males as the more variable sex."[4]

Early controversies in the 20th century

The publication of Ellis's Man and Women led to an intellectual dispute about the variability hypothesis between Ellis and the renowned statistician Karl Pearson, whose critique of Ellis's work was both theoretical and methodological. After Pearson dismissed Ellis's conclusions, he then "presented his own data to show that it was the female who was more variable than the male"[5] Ellis wrote a letter to Pearson thanking him for the criticisms which would allow him to present his arguments "more clearly & precisely than before", but did not yield his position regarding greater male variability (Ibid pp. 777 - 778).

Support for the greater male variability hypothesis grew during the early part of the 20th century.[6] During this period, the attention of researchers shifted towards studying variability in mental abilities partly due to the advent of standardised mental tests (see the history of the Intelligence quotient), which made it possible to examine intelligence with greater objectivity and precision.

One advocate of greater male variability during this time was the American psychologist Edward Thorndike, one of the leading exponents of mental testing who played an instrumental role in the development of today's Armed Services Vocational Aptitude Battery ASVAB. In his 1906 publication Sex in Education, Thorndike argued that while mean level sex differences in intellectual ability appeared to be negligible, sex differences in variability were clear [7]. Other influential proponents of the hypothesis at this time were psychologists G. Stanley Hall and James McKeen Cattell.[8][9][10]. Thorndike believed that variability in intelligence could have a biological basis and suggested that this could have important implications for achievement and pedagogy. For example, he postulated that greater male variation could mean "eminence and leadership of the world's affairs of whatever sort will inevitably belong oftener to men"[11] (Hollingsworth, 1914, p. 511). In addition, since the number of women that fall within the extreme top-end of the intelligence distribution would be inherently smaller, he suggested that educational resources should be invested in preparing women for roles and occupations that require only a mediocre level of cognitive ability [12].

Leta Hollingworth's studies

See also: Leta Hollingworth

By examining the case records of 1,000 patients at the Clearing House for Mental Defectives, Leta Hollingworth determined that, although men outnumbered women in the clearing house, the ratio of men to women decreased with age. Hollingworth explained this to be the result of men facing greater societal expectations than women. Consequently, deficiencies in men were often detected at an earlier age, while similar deficiencies in women might not be detected because less was expected of them. Therefore, deficiencies in women would be required to be more pronounced than those in men in order to be detected at similar ages.[8][9][12][13][10]

Hollingworth also attacked the variability hypothesis theoretically, criticizing the underlying logic of the hypothesis.[8][9][12][14] Hollingworth argued that the variability hypothesis was flawed because: (1) it had not been empirically established that men were more anatomically variable than women, (2) even if greater anatomical variability in men were established this would not necessarily mean that men were also more variable in mental traits, (3) even if it were established that men were more variable in mental traits this would not automatically mean that men were innately more variable, (4) variability is not significant in and of itself, but rather depends on what the variability consists of, and (5) that any possible differences in variability between men and women must also be understood with reference to the fact that women lack the opportunity to achieve eminence because of their prescribed societal and cultural roles.[8][9][12] Additionally, the argument that great variability automatically meant greater range was criticized by Hollingworth.[12][15][how?]

In an attempt to examine the validity of the variability hypothesis, while avoiding intervening social and cultural factors, Hollingworth gathered data on birth weight and length of 1,000 male and 1,000 female newborns. This research found virtually no difference in the variability of male and female infants, and it was concluded that if variability "favoured" any sex it was the female sex.[8][9][12][13] Additionally, along with the anthropologist Robert Lowie, Hollingworth published a review of literature from anatomical, physiological, and cross-cultural studies, in which no objective evidence was found to support the idea of innate female inferiority.[8][9][12][15][14]

Modern studies

The 21st century has witnessed a resurgence of research on gender differences in variability, with most of the emphasis on humans. The results vary based on the type of problem, but some recent studies have found that the variability hypothesis is true for parts of IQ tests, with more men falling at the extremes of the distribution.[16][17] Publications differ as to the extent and distribution of male variability, including on whether variability can be shown across various cultural and social factors.[18][19][20]

A 2007 meta-analysis found that males are more variable on most measures of quantitative and visuospatial ability.[21]

A 2008 analysis of test scores across 41 countries published in Science concluded that "data shows a higher variance in boys' than girls' results on mathematics and reading tests in most OECD countries" with the results implying that "gender differences in the variance of test scores are an international phenomenon".[22]

Recent studies indicate that greater male variability in mathematics persists in the U.S., although the ratio of boys to girls at the top end of the distribution is reversed in some specific immigrant groups.[23] A 2010 meta-analysis of 242 studies found that males have an 8% greater variance in mathematical abilities than females.[24]

A 2014 review found that males tend to have higher variance on mathematical and verbal abilities but females tend to have higher variance on fear and emotionality; however, the differences in variance are small and the causes remain unknown.[25] A 2005 meta-analyses found greater female variability on the standard Raven's Progressive Matrices, and no difference in variability on the advanced progressive matrices, but also found that males had a higher average general intelligence.[26]

A 2016 study by Baye and Monseur examining twelve databases from the International Association for the Evaluation of Educational Achievement and the Program for International Student Assessment, were used to analyse gender differences within an international perspective from 1995 to 2015, and concluded, "The 'greater male variability hypothesis' is confirmed."[27] This study found that on average, boys showed 14% greater variance than girls in science, reading, and math test scores. In reading, boys were significantly represented at the bottom of score distribution, whereas for maths and science they featured more at the top. Contrary to the findings of an earlier meta-analysis published in the 1990s, where "No consistent gender differences (variance ratios) were found across countries",[28] Baye and Monseur found that greater male variability was virtually universal across nations.

These results have been replicated and expanded in a 2019 meta-analytical extension published by Helen Gray and her associates, which found that policies leading to greater female participation in the workforce tended to increase female variability and, therefore, decrease the variability gap.[29]

Contemporary controversies

The variability hypothesis has continued to spur controversy within academic circles. One of the most prominent incidents occurred in 2005 when then Harvard President, Larry Summers, addressed the National Bureau of Economic Research Conference on the subject of gender diversity in the science and engineering professions, saying that "[i]t does appear that on many, many different human attributes - height, weight, propensity for criminality, overall IQ, mathematical ability, scientific ability - there is relatively clear evidence that whatever the difference in means - which can be debated - there is a difference in the standard deviation, and variability of a male and a female population."[30][31] His remarks caused a backlash; Summers faced a non-confidence vote from the Faculty of Arts and Sciences, prompting his resignation as President.[32]

See also

References

  1. ^ Johnson, Wendy; Carothers, Andrew; Deary, Ian J. (2008-11-01). "Sex Differences in Variability in General Intelligence: A New Look at the Old Question". Perspectives on Psychological Science. 3 (6): 518–531. CiteSeerX 10.1.1.605.5483. doi:10.1111/j.1745-6924.2008.00096.x. ISSN 1745-6916. PMID 26158978.
  2. ^ Darwin, C. (1871). The descent of man and selection in relation to sex (1st ed.). London: John Murray. Retrieved 15 March 2019.
  3. ^ Ellis, H. (1894). Man and women: A study of human sexual characters (1st ed.). London: Walter Scott. Retrieved 15 March 2019.
  4. ^ Shields, S. (1982). "The variability hypothesis: The history of a biological model of sex differences in intelligence". Signs. 7 (4): 769–797. doi:10.1086/493921. JSTOR 3173639.
  5. ^ Shields, S. (1982). "The variability hypothesis: The history of a biological model of sex differences in intelligence". Signs. 7 (4): 769–797. doi:10.1086/493921. JSTOR 3173639.
  6. ^ Johnson, Wendy; Carothers, Andrew; Deary, Ian J. (2008-11-01). "Sex Differences in Variability in General Intelligence: A New Look at the Old Question". Perspectives on Psychological Science. 3 (6): 518–531. CiteSeerX 10.1.1.605.5483. doi:10.1111/j.1745-6924.2008.00096.x. ISSN 1745-6916. PMID 26158978.
  7. ^ Johnson, Wendy; Carothers, Andrew; Deary, Ian J. (2008-11-01). "Sex Differences in Variability in General Intelligence: A New Look at the Old Question". Perspectives on Psychological Science. 3 (6): 518–531. CiteSeerX 10.1.1.605.5483. doi:10.1111/j.1745-6924.2008.00096.x. ISSN 1745-6916. PMID 26158978.
  8. ^ a b c d e f Benjamin, L. T. (1975). The pioneering work of Leta Hollingworth in the psychology of women. Nebraska History, 56, 493-505.
  9. ^ a b c d e f Benjamin, L. T. (1990). Leta Stetter Hollingworth: Psychologist, educator, feminist. Roeper Review, 12, 145-151.
  10. ^ a b Shields, S. A. (1991). Leta Stetter Hollingworth: "Literature of Opinion" and the study of individual differences. In G. A. Kimble, M. Wertheimer, and C. White (Eds.), Portraits of pioneers in psychology (pp.243-255). Washington, DC: American Psychological Association.
  11. ^ Hollingworth, L. S. (1914). "Variability as related to sex differences in achievement: A critique". American Journal of Sociology. 19 (4): 510–530. doi:10.1086/212287.
  12. ^ a b c d e f g Shields, S. A. (1975). Ms. Pilgrim’s Progress: The contributions of Leta Stetter Hollingworth to the psychology of women. American Psychologist, 30, 852-857.
  13. ^ a b Benjamin, L. T., & Shields, S. A. (1990). Leta Stetter Hollingworth (1886-1939). In A. N. O’Connell & N. F. Russo (Eds.), Women in psychology: A bio-bibliographic sourcebook (pp.173-183). Westport, Connecticut: Greenwood.
  14. ^ a b Poffenberger, A. T. (1940). Leta Stetter Hollingworth: 1886-1939. The American Journal of Psychology, 53, 299-301.
  15. ^ a b Denmark, F. L., & Fernandez, L. C. (1993). Historical development of the psychology of women. In F. L. Denmark & M. A. Paludi (Eds.), Psychology of women: A handbook of issues and theories (pp. 1-22). Westport, Connecticut: Greenwood.
  16. ^ Machin, S.; Pekkarinen, T. (2008). "Global Sex Differences in Test Score Variability". Science. 322 (5906): 1331–2. doi:10.1126/science.1162573. PMID 19039123.
  17. ^ Hedges, Larry V.; Nowell, Amy (1995). "Sex Differences in Mental Test Scores, Variability, and Numbers of High-Scoring Individuals". Science. 269 (5220): 41–45. Bibcode:1995Sci...269...41H. doi:10.1126/science.7604277. PMID 7604277.
  18. ^ Feingold, Alan (1994-01-01). "Gender differences in variability in intellectual abilities: A cross-cultural perspective". Sex Roles. 30 (1–2): 81–92. doi:10.1007/BF01420741. ISSN 0360-0025.
  19. ^ Penner, Andrew M. (2008-11-01). "Gender Differences in Extreme Mathematical Achievement: An International Perspective on Biological and Social Factors". American Journal of Sociology. 114 (S1): S138–S170. doi:10.1086/589252. JSTOR 10.1086/589252. PMID 19569403.
  20. ^ Hyde, Janet S.; Mertz, Janet E. (2009-06-02). "Gender, culture, and mathematics performance". Proceedings of the National Academy of Sciences. 106 (22): 8801–8807. Bibcode:2009PNAS..106.8801H. doi:10.1073/pnas.0901265106. ISSN 0027-8424. PMC 2689999. PMID 19487665.
  21. ^ Halpern, Diane F. et all. "The Science of Sex Differences in Science and Mathematics." Psychological Science in the Public Interest. Volume: 8 issue: 1, page(s): 1-51, Issue published: August 1, 2007. https://doi.org/10.1111/j.1529-1006.2007.00032.x. http://journals.sagepub.com/doi/10.1111/j.1529-1006.2007.00032.x
  22. ^ Machin, Stephen; Pekkarinen, Tuomas (2008-11-28). "Global Sex Differences in Test Score Variability". Science. 322 (5906): 1331–1332. doi:10.1126/science.1162573. ISSN 0036-8075. PMID 19039123.
  23. ^ Hyde, Janet S.; Lindberg, Sara M.; Linn, Marcia C.; Ellis, Amy B.; Williams, Caroline C. (2008-07-25). "Gender Similarities Characterize Math Performance". Science. 321 (5888): 494–495. doi:10.1126/science.1160364. ISSN 0036-8075. PMID 18653867.

    "Greater male variance is indicated by VR > 1.0. All VRs, by state and grade, are >1.0 [range 1.11 to 1.21 (see top table on p. 494)]. Thus, our analyses show greater male variability, although the discrepancy in variances is not large"
  24. ^ Lindberg, Sara M.,Hyde, Janet Shibley,Petersen, Jennifer L.,Linn, Marcia C. "New trends in gender and mathematics performance: A meta-analysis." Psychological Bulletin, Vol 136(6), Nov 2010, 1123-1135. http://psycnet.apa.org/doiLanding?doi=10.1037%2Fa0021276.
  25. ^ Hyde, Janet Shibley. "Gender Similarities and Differences." The Annual Review of Psychology. 2014. 65:3.1–3.26 doi: 10.1146/annurev-psych-010213-115057. https://www.gwern.net/docs/iq/2014-hyde.pdf.
  26. ^ Irwing, Paul. Lynn, Richard. "Sex differences in means and variability on the progressive matrices in university students: A meta‐analysis." British Journal of Psychology. Volume96, Issue 4 November 2005 Pages 505-524. https://doi.org/10.1348/000712605X53542 .
  27. ^ Baye, Ariane; Monseur, Christian (2016). "Gender differences in variability and extreme scores in an international context". Large-Scale Assessments in Education. 4 (4): 1–16. doi:10.1186/s40536-015-0015-x.
  28. ^ Feingold, A. (1994). "Gender differences in variability in intellectual abilities: A cross-cultural perspective". Sex Roles. 30 (1–2): 81–92. doi:10.1007/BF01420741.
  29. ^ Gray, H., Lyth, A., McKenna, C., Stothard, S., Tymms, P., & Copping, L. (2019). "Sex differences in variability across nations in reading, mathematics and science: a meta-analytic extension of Baye and Monseur (2016)". Large-Scale Assessments in Education. 7 (1): 2–29. doi:10.1186/s40536-019-0070-9. Taken together, it suggests that cultural practices tied to increasing female participation generally appear to increase variances for females and suggests that greater male variance in educational outcomes may be practically reduced on national levels.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  30. ^ "Full Transcript: President Summers' Remarks at the National Bureau of Economic Research, Jan. 14 2005". The Harvard Crimson. Retrieved 2 July 2019.
  31. ^ "What Larry Summers Said". www.insidehighered.com. Retrieved 2020-05-31.
  32. ^ Finder, A., Healy, P. D., & Zernike, P. (2006) (2006-02-22). "President of Harvard Resigns, Ending Stormy 5-Year Tenure". New York Times. Retrieved 2 July 2019.{{cite news}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)
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